| Arithmetic ability is an important high-level cognitive function.Recently,accumulating evidence indicates that successful performance on high-level cognitive function requires not only local properties of particular brain regions but also the interactions among multiple brain regions.However,most previous studies on arithmetic development have focused on functional activity and structural properties in local brain areas.It remains largely unknown whether and how functional or structural connectivity among large-scale brain networks contribute to arithmetic development in school-age children.Therefore,based on a two-year longitudinal public data set of 63 typically developing children,we constructs brain functional network and structural covariant network separately to explore the brain mechanisms supporting arithmetic development.In the first study,we used task-state f MRI and graph theory to investigate the longitudinal development of large-scale brain networks for an arithmetic task in younger(mean age 10 at time 1)and older children(mean age 12 at time 1),respectively.The results showed that the default-mode(DMN)and frontal-parietal networks(FPN)became increasingly segregated over time.Specifically,intra-connectivity within the DMN and FPN increased significantly with age,and inter-connectivity between the DMN and visual network decreased significantly with age.Such developmental changes were mainly observed in the younger children but not in the older children.Moreover,the change in network segregation of the DMN was positively correlated with longitudinal gain in arithmetic performance in the younger children,and individual difference in network segregation of the FPN was positively correlated with arithmetic performance at Time 2 in the older children.These results suggest that modular segregation of task-dependent functional brain networks contributes to the development of arithmetic ability in school-age children.In the second study,we used structural MRI data at time 1(mean age = 11)and arithmetic data at both time points to investigate whether early gray matter structural covariance contributes to later gain in arithmetic ability in school-age children.Mean gray matter volumes were extracted from eight brain regions of interest to anchor salience network(SN),FPN,motor network(MN)and DMN at Time 1.We found that longitudinal gain in arithmetic ability was associated with stronger structural covariance of the SN seed with frontal and parietal regions,and stronger structural covariance of the FPN seed with insula,but weaker structural covariance of the FPN seed with motor and temporal regions,weaker structural covariance of the MN seed with frontal and motor regions,and weaker structural covariance of the DMN seed with temporal region.However,we did not detected correlation between longitudinal gain in arithmetic ability with behavioral measure or regional gray matter volume at Time 1.These results provides novel evidence for a specific contribution of gray matter structural covariance to longitudinal gain in arithmetic ability in childhood.Taken together,the present results suggest that the development of arithmetic ability is closely related to both the functional and structural architecture in large-scale brain networks,which may provide insights into potential neural mechanisms underlying academic ability development. |
